Head of Quantitative Modelling & Research

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Job Description:

Roles & Responsibilities

Options Market Making, Calibration & Smile Modeling

  • Develop and own the quantitative infrastructure for quoting and risk managing vanilla and exotic options, including:

  • Real-time volatility surfaces

  • Greeks engines

  • Market-making and execution algorithms

  • Lead implementation of arbitrage-free volatility smile and skew models, including:

  • Smile parameterisation techniques: e.g. SVI, SABR, and Fengler’s arbitrage-free smoothing approaches

  • Local volatility models: Dupire local volatility for smile-consistent pricing and delta-hedging

  • Mixed local/stochastic volatility models: for capturing dynamic skew behaviour under stressed conditions

  • Build robust model calibration pipelines to liquid market instruments (e.g. vanilla options, forwards, futures) ensuring:

  • Fast convergence

  • Numerical stability

  • No calendar, butterfly, or vertical spread arbitrage

  • Extend volatility modelling to handle long-dated exotic derivatives:

  • American barriers, Asian accumulators, spread options, TARFs

  • Currency-denominated option structures with quanto and correlation features

Term Structure & Correlation Modelling

  • Develop multi-factor forward curve models for commodities and currencies:

  • Gabillon Two-Factor Model for capturing commodity forward curve dynamics

  • Schwartz-Smith or CIR++ extensions for interest rate and inflation-linked exposure

  • Model and estimate cross-asset correlations, particularly between:

  • Commodities (oil, palm, soy, energy, etc.)

  • Currencies (USD, CNY, MYR, INR, etc.)

  • Freight and storage costs

  • Integrate correlation modeling into:

  • Structured products

  • Portfolio VaR / CVaR frameworks

  • Basis risk hedging strategies

Real Assets & Physical Optionality

  • Build stochastic optimization and valuation frameworks for:

  • Crushing/refining spreads (e.g. soybean crush, palm kernel crush)

  • Storage and logistics assets as American swing options

  • Real-time asset monetization tools using Monte Carlo simulation, real options valuation, and basis path modeling

  • Incorporate physical constraints (capacity, delivery time, transport) into derivatives-driven optimization

Ideal Candidate

  • PhD or Master’s in a quantitative field (Mathematics, Financial Engineering, Physics, Computer Science)

  • Background in commodities markets (energy, agri, metals)

  • Experience building physical-real optionality models

  • Exposure to algorithmic quoting engines and real-time market data feeds

  • Understanding of machine learning techniques for market regime switching or signal generation

  • 10+ years of experience in:

  • Quantitative research for derivatives trading or market making

  • Building volatility surfaces, smile models, and calibration tools

  • Exotic option pricing in commodity, currency, or hybrid markets

To apply, please submit your resume and cover letter outlining your interest for this role.

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